AI Conversation Logger

AI Conversation Logger MCP

An intelligent MCP (Model Context Protocol) server designed specifically for AI assistants to automatically log and manage conversation history with developers.

🎯 Core Features

🤖 AI-Driven Logging - All content is determined and provided by the AI assistant
📝 Pure Save Mode - MCP only formats and stores, no content extraction or analysis
🔄 Designed for AI Retrospection - Log format optimized for AI to quickly understand project history
🏷️ Smart Organization - Auto-organize by project and date with tagging support
🔍 Powerful Search - Multi-dimensional search by keywords, files, tags, and time range
📊 Context Suggestions - Smart recommendations based on file associations

🚀 Quick Start

1. Install Dependencies

npm install

2. Build Project

npm run build

3. Configure Claude Code

Add MCP server configuration to Claude Code's config file (~/.claude.json):

{
  "mcpServers": {
    "conversation-logger": {
      "command": "node",
      "args": ["/path/to/ai-conversation-logger-mcp/dist/index.js"]
    }
  }
}

4. Restart Claude Code

Restart Claude Code to apply the configuration.

📚 API Tools

1. log_conversation - Core Logging Tool

Records every AI-user interaction with structured information:

interface LogConversationParams {
  userRequest: string;      // User's original request + uploaded file descriptions
  aiTodoList: string[];     // AI's execution plan (list even for view-only tasks)
  aiSummary: string;        // AI's operation summary (3-5 sentences)
  fileOperations?: string[]; // File operations in format: "action filepath - description"
  title?: string;           // Conversation title (optional)
  tags?: string[];          // Tag array (optional)
  project?: string;         // Project name (auto-detected if not provided)
}

2. search_conversations - Search Tool

Search through conversation history with multiple filters:

interface SearchParams {
  keywords?: string[];     // Keyword search
  filePattern?: string;    // File name pattern search
  days?: number;          // Recent N days
  project?: string;       // Project filter (defaults to current)
  tags?: string[];        // Tag filter
  limit?: number;         // Result limit (default: 10)
}

3. get_context_suggestions - Context Recommendations

Get relevant historical context based on current work:

interface ContextParams {
  currentInput: string;    // Current user input
  currentFiles?: string[]; // Currently involved files
  project?: string;        // Project filter (optional)
}

📁 Storage Structure

Logs are stored in the project's ai-logs/ directory:

project-root/
├── ai-logs/
│   ├── 2025-08-07.md     # Daily conversation logs
│   ├── 2025-08-06.md
│   └── config.json       # Project configuration
├── src/
└── ...

📝 Log Format

Each conversation is recorded with the following structure:

## [Timestamp] Title #tags

### 🗣️ User Request
[Original user request]

### 📋 AI Execution Plan
- [x] Completed task
- [ ] Pending task

### 🤖 AI Summary
[Summary of what was accomplished]

### 📂 File Operations
- **Created** `path/to/file` - Purpose description
- **Modified** `path/to/file` - What was changed
- **Deleted** `path/to/file` - Reason for deletion

### 🏷️ Tags
#module #technology #type

🎯 Usage Principles

When to Log

All conversations should be logged, including:

New feature development
Bug fixes (any size)
Code refactoring
Configuration changes
Code explanations and analysis
Technical Q&A
Code reviews
Any project-related dialogue

Key Points

AI-Driven Content - AI determines what information to log
Complete Context - Include all relevant details for future reference
Focus on "What" not "How" - Emphasize functionality over technical details
Consistent Format - Maintain standardized markdown structure

🛠️ Development

Development Mode

npm run dev

Run Tests

npm test

Code Linting

npm run lint
npm run lint:fix

TypeScript Check

npm run type-check

🔧 Technical Stack

TypeScript - Type-safe development
MCP SDK - Model Context Protocol implementation
Node.js - Runtime environment
Jest - Testing framework

📄 License

MIT

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

📮 Contact

For issues or suggestions, please open an issue on GitHub.

Install Server

HTTP connection URL

security – no known vulnerabilities

license - not found

quality - confirmed to work

How are these scores calculated?

hybrid server

The server is able to function both locally and remotely, depending on the configuration or use case.

Tools

Enables AI assistants to automatically log and manage conversation history with developers in structured markdown format. Provides powerful search and context suggestions to help AI understand project history and maintain continuity across sessions.

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